Michael Man

1.4k citations
24 papers · 1.0k · h-index 16

Impact in

  • Oncology top 10%
    • Pancreatic and Hepatic Oncology Research
    • Cancer Cells and Metastasis
    • Cancer Immunotherapy and Biomarkers
    • Statistical Methods in Clinical Trials

Papers in

    • Gene expression and cancer classification 3
    • TGF-β signaling in diseases 2
    • Pharmacogenetics and Drug Metabolism 3

Michael Man

24 papers receiving 1.0k citations

Peers

Michael Man
Comparison fields: 5 of 120
  • Oncology 313
  • Statistics and Probability 90
  • Pharmacology 82
  • Cancer Research 98
  • Immunology 129
Replace Nenad Sarapa with:
Nenad Sarapa United States
Mark Penney United Kingdom
Jason R. Manro United States
Marisa W. Medina United States
Dennie V. Jones United States
Stephen J. Iturria United States
Mei‐Lan Liu China
Yow‐Ming Wang United States
Wendy A. Teft Canada
Jürgen Dippon Germany
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Citations per field
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Nenad Sarapa · 1×
Citations per year

Countries citing papers authored by Michael Man

Since Specialization
Citations

This map shows the geographic impact of Michael Man's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Man with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Man more than expected).

Fields of papers citing papers by Michael Man

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Man. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Man. The network helps show where Michael Man may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Man, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Man Line = papers co-authored together Michael Man links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010173
2 2021157
3 2000128
4 2015111
5 201978
6 202049
7 200746
8 202343
9 200443
10 200240
11 200731
12 201926
13 201725
14 201523
15 200620
16 201616
17 200412
18 20137
19 20186
20 20184

About Michael Man

Michael Man is a scholar working on Molecular Biology, Pharmacology, Statistics and Probability, Oncology and Surgery, having authored 24 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (4 papers), Statistical Methods in Clinical Trials (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Gene expression and cancer classification (3 papers), Statistical Methods and Inference (3 papers), Pancreatic and Hepatic Oncology Research (2 papers), TGF-β signaling in diseases (2 papers) and Lipoproteins and Cardiovascular Health (2 papers). The work is most often cited by research in Oncology (313 citations), Statistics and Probability (90 citations), Pharmacology (82 citations), Cancer Research (98 citations) and Immunology (129 citations). Michael Man has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Xuning Wang, Yixin Wang, Wei‐Yin Loh, Xu He, Karim A. Benhadji, Shawn T. Estrem, Sandra Close, Gyu Jeong Noh, Shin Irie and Carmen M. Dumaual. Their work appears in journals such as Statistics in Medicine, PLoS ONE, BMC Cancer, Journal of Clinical Oncology and BMC Genetics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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